scholarly journals An Up-Down Bit Pattern Approach to Coregulated and Negative-Coregulated Gene Clustering of Microarray Data

2011 ◽  
Vol 18 (12) ◽  
pp. 1777-1791
Author(s):  
Jiun-Rung Chen ◽  
Ye-In Chang
Keyword(s):  
Microarray Data ◽  
Gene Clustering ◽  
Pattern Approach ◽  
Coregulated Gene

scholarly journals Time-dependent changes in ARE-driven gene expression by use of a noise-filtering process for microarray data

2002 ◽  
Vol 9 (3) ◽  
pp. 137-144 ◽  
Author(s):  
Jiang Li ◽  
Jeffrey A. Johnson
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Microarray Data ◽  
Transcriptional Activation ◽  
Expression Profiles ◽  
Time Dependent ◽  
Gene Clustering ◽  
Noise Filtering ◽  
Human Neuroblastoma ◽  
Rank Analysis

The current study was designed to identify the time-dependent gene expression profiles of antioxidant responsive element (ARE)-driven genes induced by tert-butylhydroquinone (tBHQ). A set of simple noise-filtering methods was introduced to evaluate and minimize the variance of microarray datasets. Gene expression induced by tBHQ (10 μM) in IMR-32 human neuroblastoma cells was analyzed by means of large-scale oligonucleotide microarray. Rank analysis was used to determine the acceptable number of independent samples necessary to eliminate false positives from the dataset. A dramatic reduction in the number of genes passing the rank analysis was achieved by using a 3 × 3 matrix comparison. Reproducibility was evaluated based on the coefficient of variation for average difference change. Completion of these analyses revealed that 101 of the 9,670 genes examined showed dynamic changes with treatment ranging from 4 h to 48 h. Since certain ARE-driven genes have been already identified, gene clustering would presumably group them together based on similar regulation. Self-organizing map grouped the genes induced by tBHQ into 12 (4×3) distinct clusters. Those previously identified ARE-driven genes were shown to group into different clusters. Since all potential ARE-driven genes did not cluster together, we speculate that multiple transcription factors and/or multiple signal transduction pathways contribute to transcriptional activation of the ARE. In conclusion, many novel potential ARE-driven genes were identified in this study. They function in detoxification and antioxidant defense, neuronal proliferation and differentiation, and signal transduction. The noise-filtering process applied to these microarray data, therefore, has proven to be very useful in identification of the time-dependent changes in ARE-drive gene expression.

A simple method to extract specific signature genes and relevant algorithms of gene clustering from pangenomic microarray data sets

2006 ◽  
Vol 164 ◽  
pp. S296
Author(s):  
Carine Lambert ◽  
Catherine Spire ◽  
Dominique Bazot ◽  
Andre Guillouzo ◽  
Nancy Claude
Keyword(s):  
Microarray Data ◽  
Gene Clustering ◽  
Data Sets ◽  
Simple Method ◽  
Signature Genes

Interactive Gene Clustering—A Case Study of Breast Cancer Microarray Data

2006 ◽  
Vol 8 (1) ◽  
pp. 21-27 ◽  
Author(s):  
Alicja Gruźdź ◽  
Aleksandra Ihnatowicz ◽  
Dominik Ślʁzak
Keyword(s):  
Breast Cancer ◽  
Microarray Data ◽  
Gene Clustering

Maximal Subspace Coregulated Gene Clustering

2008 ◽  
Vol 20 (1) ◽  
pp. 83-98 ◽  
Author(s):  
Yuhai Zhao ◽  
J.X. Yu ◽  
Guoren Wang ◽  
Lei Chen ◽  
Bin Wang ◽  
...  
Keyword(s):  
Gene Clustering ◽  
Coregulated Gene

Personality and creativity: A pattern approach

2009 ◽  
Author(s):  
Justin Yurkovich ◽  
Roni Reiter-Palmon ◽  
Joseph M. James
Keyword(s):  
Pattern Approach

Expression and network analysis of Illumina microarray data

2009 ◽  
Author(s):  
Giovanni Coppola ◽  
Kellen Winden ◽  
Genevieve Konopka ◽  
Fuying Gao ◽  
Daniel Geschwind
Keyword(s):  
Network Analysis ◽  
Microarray Data

The tyrosine kinase TEK is differentially expressed in non-small cell lung adenocarcinomas.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
United States ◽  
Tyrosine Kinase ◽  
Lung Adenocarcinoma ◽  
Microarray Data ◽  
The United States ◽  
Small Cell ◽  
Small Cell Lung ◽  
Significant Differential Expression ◽  
Lung Cancers ◽  
Lung Adenocarcinomas

Non-small cell lung adenocarcinoma (NSCLC) is a leading cause of death in the United States and worldwide (1, 2). We mined published microarray data (3, 4, 5) to discover genes associated with NSCLC. We identified significant differential expression of the tyrosine kinase TEK in tumors from patients with NSCLC. TEK may be of relevance to the initiation, progression or maintenance of non-small cell lung cancers.

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